Non-negative matrix factorization for the near real-time interpretation of absorption effects in elemental distribution images acquired by X-ray fluorescence imaging

Alfeld, Matthias; Wahabzada, Mirwaes; Bauckhage, Christian; Kersting, Kristian; Wellenreuther, Gerd; Barriobero-Vila, Pere; Requena, Guillermo; Boesenberg, Ulrike; Falkenberg, Gerald

doi:10.1107/s1600577515023528

Cited by 19 publications

(4 citation statements)

References 26 publications

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“…In particular, given the non‐negative nature of counts in the X‐ray spectra, the non‐negative matrix analysis (NNMA) has been carried out, resulting in a set of new XRF spectra and a corresponding set of new XRF images [25–27] …”

Section: Resultsmentioning

confidence: 99%

In situ macro X‐Ray fluorescence scanning on a Leonardo da Vinci portrait

et al. 2020

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Recently, an oil‐on‐panel painting, portraying Leonardo da Vinci, was found in the monastery of Camaldoli (Arezzo, Italy). The painting comes from a private donation and, over time, it never was moved from the monastery or loaned to museums or art galleries for exhibitions. Historians hypothesise that the painting could be a seventeenth‐century copy of a portrait or a self‐portrait of Leonardo da Vinci. Although, almost certainly, the panel was not signed by Leonardo, it raised a great interest for art experts, since the copy could be the outstanding testimony left to us of an original Leonardo's masterpiece, which is gone lost. The ICRCPAL in Rome, in collaboration with the ISPC‐CNR and the INFN‐LNS of Catania, started a scientific investigation of the painting based on the use of non‐invasive techniques. Macro X‐ray fluorescence imaging technique (MA‐XRF) was employed to document, for the first time, the nature of original pigments composing the pictorial and priming layers. The results allowed to better elucidate the painting technique, also to know the original look of degraded areas, suggesting an appropriate restoration and conservation policy. Novel information has been obtained concerning the pictorial process, since elemental distribution maps revealed an underpainting below the Leonardo portrait. Despite the cleaning process of the panel before its reuse, some pictorial details remained visible to the MA‐XRF analysis, allowing to infer the presumed figure hidden behind the figure of Leonardo.

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Section: Resultsmentioning

confidence: 99%

In situ macro X‐Ray fluorescence scanning on a Leonardo da Vinci portrait

et al. 2020

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“…For the purpose, the hyperspectral datacube is rearranged in a data matrix D ∈ R d×n made of n pixels, while d is the spectral dimension. The data matrix is then factorized as the product of k spectral endmembers represented by the matrix W ∈ R d×k and the abundance matrix H ∈ R k×n , which represents the contribution of each endmember to a given pixel [30]. The process is summarized as follows:…”

Section: Data Post-processing and Analysismentioning

confidence: 99%

Integrating multimodal Raman and photoluminescence microscopy with enhanced insights through multivariate analysis

Di Benedetto,

Pozzi,

Valentini

et al. 2024

J. Phys. Photonics

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This paper introduces a novel multimodal optical microscope, integrating Raman and laser-induced photoluminescence (PL) spectroscopy for the analysis of micro-samples relevant in Heritage Science. Micro-samples extracted from artworks, such as paintings, exhibit intricate material compositions characterized by high complexity and spatial heterogeneity, featuring multiple layers of paint that may be also affected by degradation phenomena. Employing a multimodal strategy becomes imperative for a comprehensive understanding of their material composition and condition. The effectiveness of the proposed setup derives from synergistically harnessing the distinct strengths of Raman and laser-induced PL spectroscopy. The capacity to identify various chemical species through the latter technique is enhanced by using multiple excitation wavelengths and two distinct excitation fluence regimes. The combination of the two complementary techniques allows the setup to effectively achieve comprehensive chemical mapping of sample through a raster scanning approach. To attain a competitive overall measurement time, we employ a short integration time for each measurement point. We further propose an analysis protocol rooted in a multivariate approach. Specifically, we employ non-negative matrix factorization as the spectral decomposition method. This enables the identification of spectral endmembers, effectively correlated with specific chemical compounds present in samples. To demonstrate its efficacy in Heritage Science, we present examples involving pigment powder dispersions and stratigraphic micro-samples from paintings. Through these examples, we show how the multimodal approach reinforces material identification and, more importantly, facilitates the extraction of complementary information. This is pivotal as the two optical techniques exhibit sensitivity to different materials. Looking ahead, our method holds potential applications in diverse research fields, including material science and biology.

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“…EDS could perform element analysis by measuring the energy of the excited X-ray photons of solid materials, for samples with less complex element distribution, this measure was efficient and stable. Besides, X-ray fluorescence analysis and X-ray photoelectron spectroscopy were also frequently applied for elemental analysis [35]. The EDS spectrum in Figure 2 represented the fluctuation of element content.…”

Section: Microstructure Characterizationmentioning

confidence: 99%

Central Composite Experiment Design (CCD)-Response Surface Method (RSM) to Optimize the Sintering Process of Ti-6Al-4V Alloy

Xia

Liu

Zhang

et al. 2021

Metals

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It is widely acknowledged that the blended elemental (BE) powder metallurgy (PM) Ti6Al4V alloy attracted unusual due to its low cost and comprehensive mechanical properties. However, the high porosity and mediocre mechanical properties of traditional vacuum sintering limited its application. To achieve better mechanical performance, the central composite designs (CCDs) method was employed to analyze the influence of sintering parameters, such as sintering temperature (St), heating rate (Hr), and holding time (Ht). The results indicated that St makes the most significant contribution to compressive strength and sintering density, accounting for 95.5% and 86.54% respectively. In addition, Ht makes the most significant contribution to compression ratio, which accounted for 89.35%. Through the analysis of response surface methodology (RSM), the optimum sintering parameters (St, Ht, Hr) could be considered to be 1300 °C, 148 min and 5 °C/min. In addition, verification experiments were carried out under the optimum conditions, and the experimental results were in good agreement with the predicted values, since the deviation of the predicted and experimental values was less than 4.9%. Therefore, the results of this study could certify the reliability of CCDs method, which would contribute to the development of titanium alloys with low cost and high mechanical properties.

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Non-negative matrix factorization for the near real-time interpretation of absorption effects in elemental distribution images acquired by X-ray fluorescence imaging

Cited by 19 publications

References 26 publications

In situ macro X‐Ray fluorescence scanning on a Leonardo da Vinci portrait

In situ macro X‐Ray fluorescence scanning on a Leonardo da Vinci portrait

Integrating multimodal Raman and photoluminescence microscopy with enhanced insights through multivariate analysis

Central Composite Experiment Design (CCD)-Response Surface Method (RSM) to Optimize the Sintering Process of Ti-6Al-4V Alloy

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